Modern industrial plants typically utilize a predictive maintenance system or a condition monitoring system for monitoring and analyzing the condition of machines in the plant. Such machines typically include electric motors, pumps, fans, gearboxes, rotating shafts, presses, welders, mixers, furnaces, conveyor systems, and other equipment. The types of parameters collected from these machines vary depending upon the type of the machine, but the typical parameters include vibration, ultrasonic vibration, temperature, voltage, current, magnetic flux, thermal profiles, and alignment data. Condition monitoring systems generate a large amount of data that is challenging for even highly skilled operators to analyze. Often, plants utilize less skilled operators to obtain condition monitoring data and perform the initial analysis. Such lesser skilled operators have even more problems in understanding the data, and a missed problem may cause expensive down time for a plant. A method and device is needed which makes it easier for operators of all levels to understand and analyze monitoring data.